Chronic ankle instability affects the association between knee joint angle and loading: musculoskeletal simulation study.

The purpose of this study was to calculate and compare (1) knee loads, (2) muscle-specific contributions to knee loads, and (3) effects of knee flexion angle on knee loads and muscle-specific load contributions during a forward jump-landing task in people with and without chronic ankle instability (CAI). Eight CAI patients and seven healthy controls performed a forward jump-landing task. We collected 3D kinematics, ground reaction force, and muscle activation and used musculoskeletal modeling. The results showed that only healthy controls exhibited an association between knee flexion angle and knee compressive impulse (r = 0.854, p = .014). The lack of association in CAI group may lead to knee instability and increase knee injury risk in people with CAI.

Prediction of medial knee contact force using multisource fusion recurrent neural network and transfer learning.

Estimation of knee contact force (KCF) during gait provides essential information to evaluate knee joint function. Machine learning has been employed to estimate KCF because of the advantages of low computational cost and real-time. However, the existing machine learning models do not adequately consider gait-related data's temporal-dependent, multidimensional, and highly heterogeneous nature. This study is aimed at developing a multisource fusion recurrent neural network to predict the medial condyle KCF. First, a multisource fusion long short-term memory (MF-LSTM) model was established. Then, we developed a transfer learning strategy based on the MF-LSTM model for subject-specific medial KCF prediction. Four subjects with instrumented tibial prostheses were obtained from the literature. The results showed that the MF-LSTM model could predict medial KCF to a certain high level of accuracy (the mean of ρ = 0.970). The transfer learning model improved the prediction accuracy (the mean of ρ = 0.987). This study shows that the MF-LSTM model is a powerful and accurate computational tool for medial KCF prediction. Introducing transfer learning techniques could further improve the prediction performance for the target subject. This coupling strategy can help clinicians accurately estimate and track joint contact forces in real time.

Monitoring Knee Contact Force with Force-Sensing Insoles.

Numerous applications exist for monitoring knee contact force (KCF) throughout activities of daily living. However, the ability to estimate these forces is restricted to a laboratory setting. The purposes of this study are to develop KCF metric estimation models and explore the feasibility of monitoring KCF metrics via surrogate measures derived from force-sensing insole data. Nine healthy subjects (3F, age 27 ± 5 years, mass 74.8 ± 11.8 kg, height 1.7 ± 0.08 m) walked at multiple speeds (0.8-1.6 m/s) on an instrumented treadmill. Thirteen insole force features were calculated as potential predictors of peak KCF and KCF impulse per step, estimated with musculoskeletal modeling. The error was calculated with median symmetric accuracy. Pearson product-moment correlation coefficients defined the relationship between variables. Models develop per-limb demonstrated lower prediction error than those developed per-subject (KCF impulse: 2.2% vs 3.4%; peak KCF: 3.50% vs. 6.5%, respectively). Many insole features are moderately to strongly associated with peak KCF, but not KCF impulse across the group. We present methods to directly estimate and monitor changes in KCF using instrumented insoles. Our results carry promising implications for internal tissue loads monitoring outside of a laboratory with wearable sensors.

Can static optimization detect changes in peak medial knee contact forces induced by gait modifications?

Medial knee contact force (MCF) is related to the pathomechanics of medial knee osteoarthritis. However, MCF cannot be directly measured in the native knee, making it difficult for therapeutic gait modifications to target this metric. Static optimization, a musculoskeletal simulation technique, can estimate MCF, but there has been little work validating its ability to detect changes in MCF induced by gait modifications. In this study, we quantified the error in MCF estimates from static optimization compared to measurements from instrumented knee replacements during normal walking and seven different gait modifications. We then identified minimum magnitudes of simulated MCF changes for which static optimization correctly identified the direction of change (i.e., whether MCF increased or decreased) at least 70% of the time. A full-body musculoskeletal model with a multi-compartment knee and static optimization was used to estimate MCF. Simulations were evaluated using experimental data from three subjects with instrumented knee replacements who walked with various gait modifications for a total of 115 steps. Static optimization underpredicted the first peak (mean absolute error = 0.16 bodyweights) and overpredicted the second peak (mean absolute error = 0.31 bodyweights) of MCF. Average root mean square error in MCF over stance phase was 0.32 bodyweights. Static optimization detected the direction of change with at least 70% accuracy for early-stance reductions, late-stance reductions, and early-stance increases in peak MCF of at least 0.10 bodyweights. These results suggest that a static optimization approach accurately detects the direction of change in early-stance medial knee loading, potentially making it a valuable tool for evaluating the biomechanical efficacy of gait modifications for knee osteoarthritis.

Erratum: Uncertainty in muscle-tendon parameters can greatly influence the accuracy of knee contact force estimates of musculoskeletal models.

[This corrects the article DOI: 10.3389/fbioe.2022.808027.].

Prediction on the medial knee contact force in patients with knee valgus using transfer learning approaches: Application to rehabilitation gaits.

The Knee contact force (KCF) is a key factor in evaluating knee joint function of patients with knee osteoarthritis. In vivo measurement of KCF based on the instrumented implants is limited due to the ethical issues and technical complexities. Machine learning can be used to predict tibiofemoral compartment contact forces. However, anthropometric differences between individuals make the accurate predictions challenging. The purpose of this study was to develop transfer learning models to predict the medial KCF of patients with knee valgus in rehabilitation gaits. Four subjects with instrumented tibial prostheses were considered, including one with knee valgus and three with normal knee joint alignment. Two transfer learning models were proposed: a fine-tuning model and an adaptive model. In particular, a synchronization method for extracting experimental data in a complete gait cycle was developed, since different types of experimental data have different sampling frequencies. The transfer learning models were pre-trained by the experiment data of patients with normal knee joint alignment, and re-trained by the data of the patient with knee valgus. Predictions of the transfer learning models and traditional machine learning model were validated against the in vivo measurements. The proposed transfer learning models were tested within two levels: the single subject (Level 1) and multiple subjects (Level 2). The results show that the two transfer learning models could more accurately predict the medial KCF of patients with knee valgus than the traditional machine learning model. The performance of the fine-tuning model is better than that of the adaptive model. Compared with the traditional machine learning and inverse dynamics analysis, transfer learning represents a much easier and more accurate method. It can be introduced to help clinicians validate and adjust the rehabilitation gait for specific patients.

Uncertainty in Muscle-Tendon Parameters can Greatly Influence the Accuracy of Knee Contact Force Estimates of Musculoskeletal Models.

Understanding the sources of error is critical before models of the musculoskeletal system can be usefully translated. Using in vivo measured tibiofemoral forces, the impact of uncertainty in muscle-tendon parameters on the accuracy of knee contact force estimates of a generic musculoskeletal model was investigated following a probabilistic approach. Population variability was introduced to the routine musculoskeletal modeling framework by perturbing input parameters of the lower limb muscles around their baseline values. Using ground reaction force and skin marker trajectory data collected from six subjects performing body-weight squat, the knee contact force was calculated for the perturbed models. The combined impact of input uncertainties resulted in a considerable variation in the knee contact force estimates (up to 2.1 BW change in the predicted force), especially at larger knee flexion angles, hence explaining up to 70% of the simulation error. Although individual muscle groups exhibited different contributions to the overall error, variation in the maximum isometric force and pathway of the muscles showed the highest impacts on the model outcomes. Importantly, this study highlights parameters that should be personalized in order to achieve the best possible predictions when using generic musculoskeletal models for activities involving deep knee flexion.

Walking-related knee contact forces and associations with knee pain across people with mild, moderate and severe radiographic knee osteoarthritis: a cross-sectional study.

OBJECTIVE: To investigate knee contact forces (KCFs), and their relationships with knee pain, across grades of radiographic knee osteoarthritis (OA) severity. DESIGN: Cross-sectional exploratory analysis of 164 participants with medial knee OA. Radiographic severity was classified as mild (grade 2), moderate (grade 3) or severe (grade 4) using the Kellgren & Lawrence (KL) scale. Walking knee pain was assessed using an 11-point numerical rating scale. External knee adduction moment (external KAM) and internal muscle forces were used to calculate medial, lateral and total KCFs using a musculoskeletal computational model. Force-time series across stance phase of gait were compared across KL grades using Statistical Parametric Mapping. Associations between KCFs and pain across KL grades were assessed using linear models. RESULTS: Medial KCFs during early and middle stance were higher in participants with KL3 and KL4 compared to those with KL2. In contrast, lateral KCFs were higher in those with KL2 compared to KL3 and KL4 in middle to late stance. The external loading component (i.e., KAM) of the medial KCF during middle to late stance was also greater in participants with KL3 and KL4 compared to those with KL2, whereas the internal (i.e., muscle) component was greater in those with KL3 and KL4 compared to KL3 during early stance. There were no associations between medial KCF and knee pain in any KL grade. CONCLUSIONS: Medial and lateral KCFs differ between mild, moderate and severe radiographic knee OA but are not associated with knee pain severity for any radiographic OA grade.

The effects of knee pain on knee contact force and external knee adduction moment in patients with knee osteoarthritis.

Knee osteoarthritis (OA) is a major cause of knee pain, leading to physical dysfunction. External knee adduction moment (KAM), a surrogate measure of knee contact force (KCF) in the medial compartment, is related to knee pain, but the association between KCF and pain severity remains unclear. This study aimed to reveal the differences in KCF due to pain severity. Twenty-eight patients with knee OA were evaluated knee symptoms including pain severity via the Knee Society Score. Based on the median symptom score, 17 points in this study, subjects were classified as having Mild symptomatic OA (n = 15) and Severe symptomatic OA (n = 13). Subjects walked three times at a comfortable speed along a six-meter walkway, and we calculated KAM during the stance phase. KCF magnitude and distribution were also computed using the subject-specific musculoskeletal model, considering physical characteristics such as the femorotibial angle measured by X-ray. No differences in physical characteristics such as femorotibial angle and gait speed were found by symptom severity, whereas KAM and medial KCF at minimum and second peak in Severe symptomatic OA patients were significantly greater than those in Mild symptomatic OA. A significant medial shift of KCF in Severe symptomatic OA was also seen at first peak and minimum. Severe symptomatic OA had a greater medial KCF and medial shift of KCF. Detailed evaluations of KCF magnitude and distribution in addition to KAM would provide crucial information on knee contact force in relation to symptom severity.

Increased Q-factor increases medial compartment knee joint contact force during cycling.

As Q-Factor (QF: inter-pedal distance) is increased, the internal knee abduction moment (KAbM) also increases, however it is unknown if this increased KAbM is associated with increased medial compartment knee joint contact force in cycling. In the absence of in vivo measurement, musculoskeletal modeling simulations may provide a viable option for estimating knee joint contact forces in cycling. The primary purpose of this study was to investigate the effect of increasing QF on knee joint total (TCF), and medial (MCF) compartment contact force during ergometer cycling. The secondary purpose was to evaluate whether KAbM and knee extension moment are accurate predictors of MCF in cycling. Musculoskeletal simulations were performed to estimate TCF and MCF for sixteen participants cycling at an original QF (150 mm), and wide QF (276 mm), at 80 W and 80 rotations per minute. Paired samples t-tests were used to detect differences between QF conditions. MCF increased significantly, however, TCF did not change at wide QF. Peak knee extensor muscle force did not change at wide QF. Peak knee flexor muscle force was significantly reduced with wide QF. Regression analyses showed KAbM and knee extension moments explained 87.4% of the variance in MCF when considered alongside QF. The increase of MCF may be attributed to increased frontal-plane pedal reaction force moment arm. Future research may seek to implement QF modulation as a part of rehabilitation or training procedures utilizing cycling in cases where medial compartment joint loading is of importance.

Higher knee contact forces might underlie increased osteoarthritis rates in high functioning amputees: A pilot study.

High functioning military transtibial amputees (TTAs) with well-fitted state of the art prosthetics have gait that is indistinguishable from healthy individuals, yet they are more likely to develop knee osteoarthritis (OA) of their intact limbs. This contrasts with the information at the knees of the amputated limbs that have been shown to be at a significantly reduced risk of pain and OA. The hypothesis of this study is that biomechanics can explain the difference in knee OA risk. Eleven military unilateral TTAs and eleven matched healthy controls underwent gait analysis. Muscle forces and joint contact forces at the knee were quantified using musculoskeletal modeling, validated using electromyography measurements. Peak knee contact forces for the intact limbs on both the medial and lateral compartments were significantly greater than the healthy controls (P ≤ .006). Additionally, the intact limbs had greater peak semimembranosus (P = .001) and gastrocnemius (P ≤ .001) muscle forces compared to the controls. This study has for the first time provided robust evidence of increased force on the non-affected knees of high functioning TTAs that supports the mechanically based hypothesis to explain the documented higher risk of knee OA in this patient group. The results suggest several protentional strategies to mitigate knee OA of the intact limbs, which may include the improvements of the prosthetic foot control, socket design, and strengthening of the amputated muscles.

Load Distribution at the Patellofemoral Joint During Walking.

We combined computational modelling with experimental gait data to describe and explain load distribution across the medial and lateral facets of the patella during normal walking. The body was modelled as a 13-segment, 32-degree-of-freedom (DOF) skeleton actuated by 80 muscles. The knee was represented as a 3-body, 12-DOF mechanical system with deformable articular cartilage surfaces at the tibiofemoral (TF) and patellofemoral (PF) joints. Passive responses of the knee model to 100 N anterior-posterior drawer and 5 Nm axial torque tests were consistent with cadaver data reported in the literature. Trajectories of 6-DOF TF and PF joint motion and articular joint contact calculated for walking were also consistent with measurements obtained from biplane X-ray imaging. The force acting on the lateral patellar facet was considerably higher than that on the medial facet throughout the gait cycle. The vastus medialis, vastus lateralis and patellar tendon forces contributed substantially to the first peak in the PF contact force during stance whereas all three portions of the vasti and rectus femoris were responsible for the second peak during swing. A higher lateral patellar contact force was caused mainly by the laterally-directed shear force applied by the quadriceps muscles, especially the vastus lateralis, intermedius and rectus femoris. A better understanding of the contributions of the individual knee muscles to load distribution in the PF compartment may lead to improved surgical and physiotherapy methods to treat PF disorders.

Influence of musculoskeletal model parameter values on prediction of accurate knee contact forces during walking.

Treatment design for musculoskeletal disorders using in silico patient-specific dynamic simulations is becoming a clinical possibility. However, these simulations are sensitive to model parameter values that are difficult to measure experimentally, and the influence of uncertainties in these parameter values on the accuracy of estimated knee contact forces remains unknown. This study evaluates which musculoskeletal model parameters have the greatest influence on estimating accurate knee contact forces during walking. We performed the evaluation using a two-level optimization algorithm where musculoskeletal model parameter values were adjusted in the outer level and muscle activations were estimated in the inner level. We tested the algorithm with different sets of design variables (combinations of optimal muscle fiber lengths, tendon slack lengths, and muscle moment arm offsets) resulting in nine different optimization problems. The most accurate lateral knee contact force predictions were obtained when tendon slack lengths and moment arm offsets were adjusted simultaneously, and the most accurate medial knee contact force estimations were obtained when all three types of parameters were adjusted together. Inclusion of moment arm offsets as design variables was more important than including either tendon slack lengths or optimal muscle fiber lengths alone to obtain accurate medial and lateral knee contact force predictions. These results provide guidance on which musculoskeletal model parameter values should be calibrated when seeking to predict in vivo knee contact forces accurately.

Effect of guided growth intervention on static leg alignment and dynamic knee contact forces during gait.

BACKGROUND: Lower limb malalignment in the frontal plane is one of the major causes of developing knee osteoarthritis. Growing children can be treated by temporary hemiepiphysiodesis when diagnosed with lower limb malalignment. RESEARCH QUESTION: Is there a difference between medial or lateral knee contact force (KCF) before (PRE) and after (POST) hemiepiphysiodesis in patients with valgus malalignment and compared to a typically developed control group (TD)? Does a linear relationship exist between the static radiographic mechanical axis angle and dynamic medial/lateral KCF? METHODS: In this prospective study, an OpenSim full body model with an adapted knee joint was used to calculate KCFs in the stance phase of 16 children with diagnosed genu valgum and 16 age- and sex-matched TDs. SPM was applied to compare KCFs before and after guided growth and to test a linear relationship between the mechanical axis angle and KCFs. RESULTS: After the intervention, POST revealed a significantly increased medial KCF (p < 0.001, 4-97 % of stance) and decreased lateral KCF (p < 0.001, 6-98 %) compared to PRE. Comparing POST with TD, short phases with a significant difference were found (medial: p = 0.039, 84-88 %; lateral: p = 0.019, 3-11 %). The static mechanical axis angle showed a longer phase of a significant relation to KCFs for POST compared to PRE. SIGNIFICANCE: This study showed that temporary hemiepiphysiodesis in patients with valgus malalignment reduces the loading in the lateral compartment of the knee and thus the risk of developing osteoarthritis in this compartment. The determination of dynamic KCFs can be clinically relevant for the treatment of lower limb malalignment, especially for decision making before surgery, when compensatory mechanisms may play an important role. Additionally, the static radiographic mechanical axis angle does not necessarily represent the dynamic loading of the lateral knee compartment.

The Capacity of Generic Musculoskeletal Simulations to Predict Knee Joint Loading Using the CAMS-Knee Datasets.

Musculoskeletal models enable non-invasive estimation of knee contact forces (KCFs) during functional movements. However, the redundant nature of the musculoskeletal system and uncertainty in model parameters necessitates that model predictions are critically evaluated. This study compared KCF and muscle activation patterns predicted using a scaled generic model and OpenSim static optimization tool against in vivo measurements from six patients in the CAMS-knee datasets during level walking and squatting. Generally, the total KCFs were under-predicted (RMS: 47.55%BW, R2: 0.92) throughout the gait cycle, but substiantially over-predicted (RMS: 105.7%BW, R2: 0.81) during squatting. To understand the underlying etiology of the errors, muscle activations were compared to electromyography (EMG) signals, and showed good agreement during level walking. For squatting, however, the muscle activations showed large descrepancies especially for the biceps femoris long head. Errors in the predicted KCF and muscle activation patterns were greatest during deep squat. Hence suggesting that the errors mainly originate from muscle represented at the hip and an associated muscle co-contraction at the knee. Furthermore, there were substaintial differences in the ranking of subjects and activities based on peak KCFs in the simulations versus measurements. Thus, future simulation study designs must account for subject-specific uncertainties in musculoskeletal predictions.

Unintended Changes in Contralateral Limb as a Result of Acute Gait Modification.

Gait modification using real-time biofeedback is a conservative intervention associated with positive outcomes. Results from systematic reviews corroborate the effectiveness of various strategies employing real-time biofeedback for reducing estimated knee joint load. The effects on the nonmodified limb, however, remain unclear. Biomechanical changes to the nonmodified limb were investigated during unilaterally implemented medial knee thrust, lateral trunk lean, and toe-in foot progression. Nineteen healthy participants were recruited. Ten trials were completed for each gait condition including baseline. Assigned magnitude for each gait modification strategy was individualized based on the mean and SD of the gait parameter during baseline. Visual real-time biofeedback was provided. During medial knee thrust, participants' nonmodified limb presented with increased: first peak medial knee contact force, internal first peak knee extensor moment, as well as knee- and hip-flexion angles at internal first peak knee extensor moment. Observed biomechanical changes are elucidative of the body's attempt to attenuate increased external loads. These findings may carry significant implications for pathological populations. Load redistribution to the nonmodified side may result in unfavorable long-term outcomes particularly in patients with bilateral diagnosis. Future studies should explore acute and chronic changes in the nonmodified limb of individuals with knee osteoarthritis.

Effects of medial collateral ligament release, limb correction, and soft tissue laxity on knee joint contact force distribution after medial opening wedge high tibial osteotomy: a computational study.

In this study, the effects of medial collateral ligament (MCL) release and the limb correction strategies with pre-existing MCL laxity on tibiofemoral contact force distribution after high tibial osteotomy (HTO) were investigated. The medial and lateral contact forces of the knee were quantified during simulated standing using computational modeling techniques. MCL slackness had a primary influence on contact force distribution of the knee, while there was little effect of simulated limb correction. Anterior and middle bundle release, which involved the partial release of two-thirds of the superficial MCL, was shown to be an optimal surgical method in HTO, achieving balanced contact distribution in simulated weight-bearing standing.

Gait alteration strategies for knee osteoarthritis: a comparison of joint loading via generic and patient-specific musculoskeletal model scaling techniques.

Gait modifications and laterally wedged insoles are non-invasive approaches used to treat medial compartment knee osteoarthritis. However, the outcome of these alterations is still a controversial topic. This study investigates how gait alteration techniques may have a unique effect on individual patients; and furthermore, the way we scale our musculoskeletal models to estimate the medial joint contact force may influence knee loading conditions. Five patients with clinical evidence of medial knee osteoarthritis were asked to walk at a normal walking speed over force plates and simultaneously 3D motion was captured during seven conditions (0°-, 5°-, 10°-insoles, shod, toe-in, toe-out, and wide stance). We developed patient-specific musculoskeletal models, using segmentations from magnetic resonance imaging to morph a generic model to patient-specific bone geometries and applied this morphing to estimate muscle insertion sites. Additionally, models were created of these patients using a simple linear scaling method. When examining the patients' medial compartment contact force (peak and impulse) during stance phase, a 'one-size-fits-all' gait alteration aimed to reduce medial knee loading did not exist. Moreover, the different scaling methods lead to differences in medial contact forces; highlighting the importance of further investigation of musculoskeletal modeling methods prior to use in the clinical setting.

Relationship between knee joint contact forces and external knee joint moments in patients with medial knee osteoarthritis: effects of gait modifications.

OBJECTIVE: To evaluate 1) the relationship between the knee contact force (KCF) and knee adduction and flexion moments (KAM and KFM) during normal gait in people with medial knee osteoarthritis (KOA), 2) the effects on the KCF of walking with a modified gait pattern and 3) the relationship between changes in the KCF and changes in the knee moments. METHOD: We modeled the gait biomechanics of thirty-five patients with medial KOA using the AnyBody Modeling System during normal gait and two modified gait patterns. We calculated the internal KCF and evaluated the external joint moments (KAM and KFM) against it using linear regression analyses. RESULTS: First peak medial KCF was associated with first peak KAM (R2 = 0.60) and with KAM and KFM (R2 = 0.73). Walking with both modified gait patterns reduced KAM (P = 0.002) and the medial to total KCF ratio (P < 0.001) at the first peak. Changes in KAM during modified gait were moderately associated with changes in the medial KCF at the first peak (R2 = 0.54 and 0.53). CONCLUSIONS: At the first peak, KAM is a reasonable substitute for the medial contact force, but not at the second peak. First peak KFM is also a significant contributor to the medial KCF. At the first peak, walking with a modified gait reduced the ratio of the medial to total KCF but not the medial KCF itself. To determine the effects of gait modifications on cartilage loading and disease progression, longitudinal studies and individualized modeling, accounting for motion control, would be required.

Knee medial and lateral contact forces in a musculoskeletal model with subject-specific contact point trajectories.

Contact point (CP) trajectory is a crucial parameter in estimating medial/lateral tibio-femoral contact forces from the musculoskeletal (MSK) models. The objective of the present study was to develop a method to incorporate the subject-specific CP trajectories into the MSK model. Ten healthy subjects performed 45 s treadmill gait trials. The subject-specific CP trajectories were constructed on the tibia and femur as a function of extension-flexion using low-dose bi-plane X-ray images during a quasi-static squat. At each extension-flexion position, the tibia and femur CPs were superimposed in the three directions on the medial side, and in the anterior-posterior and proximal-distal directions on the lateral side to form the five kinematic constraints of the knee joint. The Lagrange multipliers associated to these constraints directly yielded the medial/lateral contact forces. The results from the personalized CP trajectory model were compared against the linear CP trajectory and sphere-on-plane CP trajectory models which were adapted from the commonly used MSK models. Changing the CP trajectory had a remarkable impact on the knee kinematics and changed the medial and lateral contact forces by 1.03 BW and 0.65 BW respectively, in certain subjects. The direction and magnitude of the medial/lateral contact force were highly variable among the subjects and the medial-lateral shift of the CPs alone could not determine the increase/decrease pattern of the contact forces. The suggested kinematic constraints are adaptable to the CP trajectories derived from a variety of joint models and those experimentally measured from the 3D imaging techniques.